Immune Checkpoint Inhibitors for Mismatch Repair–Deficient Gastroesophageal Adenocarcinoma: Outcomes and Feasibility of Nonoperative Management at Mayo Clinic
PURPOSE Neoadjuvant immune checkpoint inhibitors (nICIs) have demonstrated high response rates in deficient mismatch repair/microsatellite instability–high (dMMR/MSI-H) gastroesophageal adenocarcinoma (GEA). The NEONIPIGA and INFINITY trials demonstrated high rates of pathologic complete response (pCR) in this patient population. Furthermore, the INFINITY trial explored the feasibility of managing these patients nonoperatively, demonstrating promising results. This study aimed to evaluate clinical outcomes of nICIs in resectable dMMR/MSI-H GEA, with a focus on the feasibility of nonoperative management (NOM). MATERIALS AND METHODS This retrospective cohort study included patients with resectable dMMR/MSI-H GEA and treated with nICIs ± surgery at the Mayo Clinic. Patients were identified from institutional records, and clinical data were retrospectively reviewed. Primary outcomes were clinical complete response (cCR) and pCR. Secondary outcomes included event-free survival (EFS), radiologic complete response (rCR), and immune-related adverse events (irAEs). RESULTS A total of 26 patients treated between April 1, 2017, and July 30, 2025, were identified. Nine patients (34.6%) underwent surgery, of whom six (66.7%) achieved pCR. Seventeen patients (65.4%) pursued NOM, with 10 (71.4%) of 14 evaluable patients achieving cCR and 14 (82.4%) of 17 evaluable achieving rCR. One patient who initially achieved cCR had a local recurrence on surveillance endoscopy and underwent salvage endoscopic resection. At a median follow-up of 19.3 months, 15 (88.2%) of 17 patients in the NOM cohort were alive and metastasis-free, with EFS rates of 87.3% at 12 and 24 months for all patients. irAEs occurred in nine patients (34.6%), with no grade ≥3 toxicities. CONCLUSION In this retrospective cohort study, nICIs led to high cCR and pCR rates in resectable dMMR/MSI-H GEA, supporting the use of immune checkpoint inhibitors in this setting and the feasibility of NOM in select patients.
Analysis of Tumor Microenvironmental Features Between Primary and Synchronous Liver Metastases From Patients With Colorectal Cancers Using a Deep Learning Algorithm
PURPOSE The development of colorectal liver metastases (CRLMs) is associated with poor prognosis, and recent data suggest that metastasis to the liver is associated with resistance to immunotherapy. We characterized the microenvironment of primary colorectal carcinomas (CRCs) relative to their synchronous CRLMs using a validated segmentation algorithm (QuantCRC) that quantifies 15 distinct morphologic tumor features. MATERIALS AND METHODS Adult patients with CRC with synchronous CRLM (N = 57) at Mayo Clinic were identified from the electronic health record. Routine tumor hematoxylin and eosin sections were digitized and reviewed for quality control. QuantCRC (Aiforia, Inc) was applied to digitized images to extract 15 GI pathologist predefined morphological features. Tumor features were compared between paired primary tumors and their synchronous CRLMs using the Wilcoxon signed-rank test overall and within subgroups. Linear regression models were used to find predictors of the paired differences in the distinct tumor morphological features. RESULTS The study included 57 patients (median age 59 years [IQR, 50-73], 51% female) with CRC primary and synchronous CRLM, and among primaries, 37 (65%) were left-sided. QuantCRC identified six of 15 morphological features that differed significantly between primaries and their CRLMs. Compared with the primary, CRLM showed reduced stroma, more high-grade tumor and necrosis, higher tumor–stromal ratio (TSR; all P < .05), and a trend toward increased tumor-infiltrating lymphocyte (TIL) density ( P = .052). Synchronous CRLM from patients with left-sided primary tumors had significantly higher TSR, percent high-grade, percent necrosis, and TIL density compared with the primary (all P values ≤0.04). Among right-sided primaries, CRLM had a significantly reduced percent mature stroma ( P = .0296) and a higher percent necrosis ( P = .0027). CONCLUSION Compared with the primary, synchronous CRLMs showed a higher TSR and increased high-grade tumor and necrosis, which are features of tumor aggressiveness and a metastatic phenotype.
An international inter‐rater agreement study in the challenging diagnosis of squamous dysplasia of the oesophagus
AimsThere is a lack of published literature on the diagnostic reproducibility of oesophageal squamous dysplasia using a two‐tiered grading system.Methods and resultsWe identified 75 oesophageal biopsies, which were reviewed by 10 international pathologists twice (1500 total observations) with a > 4‐week washout period. Between rounds, a consensus meeting refining diagnostic criteria was held and an atlas was created to provide illustrations. Overall agreement was fair with kappa of 0.35 and 0.32 in round 1 and 2, respectively. Agreement was moderate to fair for negative for dysplasia (ND) (round 1 = 0.41 and round 2 = 0.34) and poor for indefinite for dysplasia (IND) and low‐grade dysplasia (LGD) (kappa <0.2). Agreement for high‐grade dysplasia (HGD) was good in both rounds (round 1 = 0.64; round 2 = 0.61). In round 1, majority diagnosis (MDx, ≥6 of 10 raters agreeing) was seen in 51 (68%) cases with the majority classified as ND (N = 27) or HGD (N = 18). MDx was rarely achieved for LGD (N = 6). In round 2, MDx was seen in 49 (65%) cases (20 ND, 1 IND, 11 LGD and 17 HGD). Of the 40 cases with MDx for both rounds, 39 were concordant (15 HGD, 6 LGD and 18 ND).ConclusionsOverall agreement among pathologists in diagnosing squamous lesions is fair; however, HGD had good agreement. This study fills an important gap in our knowledge of the inter‐rater variability in the diagnosis of oesophageal squamous dysplasia.
Menopausal hormone therapy: assessing associations with breast and colorectal cancers by familial risk
Abstract Menopausal users of hormone replacement therapy (HRT) are at increased breast cancer risk and decreased colorectal cancer (CRC) risk compared with individuals who have never used HRT, but these opposing associations may differ by familial risk of breast cancer and CRC. We harmonized data from 3 cohorts and generated separate breast cancer and CRC familial risk scores based on cancer family history. We defined moderate or strong family history as a risk score of 0.4 or higher, where 0.4 was equivalent to a 50-year-old woman with 1 parent diagnosed with either breast cancer or CRC at 55 years of age. Of 24 486 women assessed, 1243 and 405 were diagnosed with incident breast cancer and CRC, respectively. For breast cancer, menopausal HRT ever use versus never use hazard ratios were 1.27 (95% CI = 1.11 to 1.45) for a breast cancer familial risk score below 0.4 and 1.01 (95% CI = 0.82 to 1.25) for a breast cancer familial risk score of 0.4 or higher (Pdifference = .08). For CRC, menopausal HRT hazard ratios were 0.63 (95% CI = 0.50 to 0.78) for a CRC familial risk score below 0.4 and 1.21 (95% CI = 0.73 to 2.00) for a CRC familial risk score of 0.4 or higher (Pdifference = .03). Associations with menopausal HRT use that apply to the general population may not hold for women at moderate or strong familial risk of these cancers.
Reliability of an Expanded Non-alcoholic Steatohepatitis Grading and Staging System for Assessment of Disease Activity and Fibrosis
The nonalcoholic steatohepatitis clinical research network (NASH-CRN) system is commonly used for histologic assessment of disease activity and fibrosis in NASH. Despite this, the system does not fully capture the range of disease activity and fibrosis. As such, an expanded NAS (E-NAS) grading and staging system with a calculated E-NAS index was developed by our group. In this follow up study, we aim to revalidate the E-NAS system and compare its reliability to existing systems. Hematoxylin and eosin and trichrome stained sections from 40 liver biopsies were reviewed digitally by four hepatopathologists and assessed using the NASH-CRN and E-NAS systems as well as a modified Ishak fibrosis stage. The pathologist's gestalt impression of disease activity and fibrosis was scored on a Visual Analogue Scale (VAS), which ranged from 0 (no activity/fibrosis) to 100 (the worst activity/fibrosis ever seen). Inter-rater reliability was assessed, and Spearman correlation coefficients were calculated. The E-NAS index had higher inter-rater agreement versus the NAS score (ICC 0.70 vs 0.61). The inter-rater agreement for ballooning in the E-NAS system was also higher at 0.67 compared to the NAS (ICC 0.60). ICCs for fibrosis were comparable between all the systems assessed (0.78 to 0.88). Finally, the calculated E-NAS index was higher with increasing stage of fibrosis compared to the NAS suggesting that it associates better with fibrosis. In summary, the E-NAS system demonstrates substantial inter-rater reliability as well as improved correlation with disease activity VAS and fibrosis compared to the NAS score.
Two genome-wide interaction loci modify the association of nonsteroidal anti-inflammatory drugs with colorectal cancer
Regular, long-term aspirin use may act synergistically with genetic variants, particularly those in mechanistically relevant pathways, to confer a protective effect on colorectal cancer (CRC) risk. We leveraged pooled data from 52 clinical trial, cohort, and case-control studies that included 30,806 CRC cases and 41,861 controls of European ancestry to conduct a genome-wide interaction scan between regular aspirin/nonsteroidal anti-inflammatory drug (NSAID) use and imputed genetic variants. After adjusting for multiple comparisons, we identified statistically significant interactions between regular aspirin/NSAID use and variants in 6q24.1 (top hit rs72833769 ), which has evidence of influencing expression of TBC1D7 (a subunit of the TSC1-TSC2 complex, a key regulator of MTOR activity), and variants in 5p13.1 (top hit rs350047 ), which is associated with expression of PTGER4 (codes a cell surface receptor directly involved in the mode of action of aspirin). Genetic variants with functional impact may modulate the chemopreventive effect of regular aspirin use, and our study identifies putative previously unidentified targets for additional mechanistic interrogation.
Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence
Abstract Deep learning may detect biologically important signals embedded in tumor morphologic features that confer distinct prognoses. Tumor morphologic features were quantified to enhance patient risk stratification within DNA mismatch repair (MMR) groups using deep learning. Using a quantitative segmentation algorithm (QuantCRC) that identifies 15 distinct morphologic features, we analyzed 402 resected stage III colon carcinomas [191 deficient (d)-MMR; 189 proficient (p)-MMR] from participants in a phase III trial of FOLFOX-based adjuvant chemotherapy. Results were validated in an independent cohort (176 d-MMR; 1,094 p-MMR). Association of morphologic features with clinicopathologic variables, MMR, KRAS, BRAFV600E, and time-to-recurrence (TTR) was determined. Multivariable Cox proportional hazards models were developed to predict TTR. Tumor morphologic features differed significantly by MMR status. Cancers with p-MMR had more immature desmoplastic stroma. Tumors with d-MMR had increased inflammatory stroma, epithelial tumor-infiltrating lymphocytes (TIL), high-grade histology, mucin, and signet ring cells. Stromal subtype did not differ by BRAFV600E or KRAS status. In p-MMR tumors, multivariable analysis identified tumor-stroma ratio (TSR) as the strongest feature associated with TTR [HRadj 2.02; 95% confidence interval (CI), 1.14–3.57; P = 0.018; 3-year recurrence: 40.2% vs. 20.4%; Q1 vs. Q2–4]. Among d-MMR tumors, extent of inflammatory stroma (continuous HRadj 0.98; 95% CI, 0.96–0.99; P = 0.028; 3-year recurrence: 13.3% vs. 33.4%, Q4 vs. Q1) and N stage were the most robust prognostically. Association of TSR with TTR was independently validated. In conclusion, QuantCRC can quantify morphologic differences within MMR groups in routine tumor sections to determine their relative contributions to patient prognosis, and may elucidate relevant pathophysiologic mechanisms driving prognosis. Significance: A deep learning algorithm can quantify tumor morphologic features that may reflect underlying mechanisms driving prognosis within MMR groups. TSR was the most robust morphologic feature associated with TTR in p-MMR colon cancers. Extent of inflammatory stroma and N stage were the strongest prognostic features in d-MMR tumors. TIL density was not independently prognostic in either MMR group.
Improved Risk-Stratification Scheme for Mismatch-Repair Proficient Stage II Colorectal Cancers Using the Digital Pathology Biomarker QuantCRC
Abstract Purpose: There is a need to improve current risk stratification of stage II colorectal cancer to better inform risk of recurrence and guide adjuvant chemotherapy. We sought to examine whether integration of QuantCRC, a digital pathology biomarker utilizing hematoxylin and eosin–stained slides, provides improved risk stratification over current American Society of Clinical Oncology (ASCO) guidelines. Experimental Design: ASCO and QuantCRC-integrated schemes were applied to a cohort of 398 mismatch-repair proficient (MMRP) stage II colorectal cancers from three large academic medical centers. The ASCO stage II scheme was taken from recent guidelines. The QuantCRC-integrated scheme utilized pT3 versus pT4 and a QuantCRC-derived risk classification. Evaluation of recurrence-free survival (RFS) according to these risk schemes was compared using the log-rank test and HR. Results: Integration of QuantCRC provides improved risk stratification compared with the ASCO scheme for stage II MMRP colorectal cancers. The QuantCRC-integrated scheme placed more stage II tumors in the low-risk group compared with the ASCO scheme (62.5% vs. 42.2%) without compromising excellent 3-year RFS. The QuantCRC-integrated scheme provided larger HR for both intermediate-risk (2.27; 95% CI, 1.32–3.91; P = 0.003) and high-risk (3.27; 95% CI, 1.42–7.55; P = 0.006) groups compared with ASCO intermediate-risk (1.58; 95% CI, 0.87–2.87; P = 0.1) and high-risk (2.24; 95% CI, 1.09–4.62; P = 0.03) groups. The QuantCRC-integrated risk groups remained prognostic in the subgroup of patients that did not receive any adjuvant chemotherapy. Conclusions: Incorporation of QuantCRC into risk stratification provides a powerful predictor of RFS that has potential to guide subsequent treatment and surveillance for stage II MMRP colorectal cancers.
Evaluating the optimum number of biopsies to assess histological inflammation in ulcerative colitis: a retrospective cohort study
SummaryBackgroundThe optimal ulcerative colitis biopsy protocol is unclear.AimTo evaluate the number of biopsies required to accurately assess microscopic disease activity in ulcerative colitisMethodsBiopsies from patients with ≥4 rectosigmoid samples, and clinical and endoscopic data, were retrospectively obtained from a prospective biobank. Histology and endoscopic videos were read blindly. A 4‐biopsy Robarts Histopathology Index (RHI) reference score, consisting of the worst item‐level ratings from four biopsies, was compared to 1‐, 2‐ and 3‐biopsy estimates. Agreement was determined using bivariate errors‐in‐variable regression analysis (acceptance interval: ±8.25). Endoscopic activity and disease location subgroup analyses were also performed.ResultsForty‐six patients had ≥4 rectosigmoid biopsies available (N = 287). The 2‐biopsy (tolerance interval: −7.66, 4.79) and 3‐biopsy (tolerance interval: −4.86, 3.46) RHI scores demonstrated acceptable agreement with 4‐biopsy scores. One‐biopsy scores demonstrated unacceptable agreement (tolerance interval: −13.99, 7.78). Mean RHI scores using the 2‐, 3‐ and 4‐biopsy approaches were similar (6.1 ± 9.6 P = 0.36; 6.8 ± 10.5, P = 0.7; 7.5 ± 11.2), whereas the 1‐biopsy estimate was lower (4.4 ± 8.1, P = 0.06). Histological remission rates were identical for the 2‐, 3‐ and 4‐biopsy methods (65.2%, P = 1.0). Subgroup analysis demonstrated that three biopsies were required in patients with endoscopically active disease. Sampling additional colonic locations yielded lower histological remission rates compared to rectosigmoid sampling alone (33.3% vs 61.9%, P = 0.1).ConclusionsA minimum of two — conservatively, three — biopsies are required to reliably assess disease activity in a single colonic segment using the RHI. Further studies are needed of endoscopically active patients and sampling locations. These results have implications for biopsy strategies in clinical trials and practice.
Using DEPendency of Association on the Number of Top Hits (DEPTH) as a Complementary Tool to Identify Novel Colorectal Cancer Susceptibility Loci
Abstract Background: DEPendency of association on the number of Top Hits (DEPTH) is an approach to identify candidate susceptibility regions by considering the risk signals from overlapping groups of sequential variants across the genome. Methods: We applied a DEPTH analysis using a sliding window of 200 SNPs to colorectal cancer data from the Colon Cancer Family Registry (CCFR; 5,735 cases and 3,688 controls), and Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO; 8,865 cases and 10,285 controls) studies. A DEPTH score > 1 was used to identify candidate susceptibility regions common to both analyses. We compared DEPTH results against those from conventional genome-wide association study (GWAS) analyses of these two studies as well as against 132 published susceptibility regions. Results: Initial DEPTH analysis revealed 2,622 (CCFR) and 3,686 (GECCO) candidate susceptibility regions, of which 569 were common to both studies. Bootstrapping revealed 40 and 49 candidate susceptibility regions in the CCFR and GECCO data sets, respectively. Notably, DEPTH identified at least 82 regions that would not be detected using conventional GWAS methods, nor had they been identified by previous colorectal cancer GWASs. We found four reproducible candidate susceptibility regions (2q22.2, 2q33.1, 6p21.32, 13q14.3). The highest DEPTH scores were in the human leukocyte antigen locus at 6p21 where the strongest associated SNPs were rs762216297, rs149490268, rs114741460, and rs199707618 for the CCFR data, and rs9270761 for the GECCO data. Conclusions: DEPTH can identify candidate susceptibility regions for colorectal cancer not identified using conventional analyses of larger datasets. Impact: DEPTH has potential as a powerful complementary tool to conventional GWAS analyses for discovering susceptibility regions within the genome.